Model comparison
Claude Fable 5 vs GPT-5.1-Codex
Claude Fable 5 is the stronger model overall, scoring 66.8 to 38.6 on the Noometry Index. GPT-5.1-Codex costs 5.8× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Summary
- They share 3 benchmarks with published results for both. Claude Fable 5 scores higher in 3 categories and GPT-5.1-Codex in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Fable 5 leads 88.5 to 30.3.
- The biggest single-benchmark swing is ProofBench: 95% for Claude Fable 5 and 9% for GPT-5.1-Codex.
- GPT-5.1-Codex is cheaper at $1.25 / $10 per million input/output tokens, against $10 / $50 for Claude Fable 5.
- Claude Fable 5 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Fable 5 | GPT-5.1-Codex | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 66.8 | 38.6 |
| Released | 2026-06-07 | 2025-11-12 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $10 | $1.25 |
| Output $ / M tokens | $50 | $10 |
| Results tracked | 62 | 6 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 70.6 (#4), GPT-5.1-Codex: 41.9 (#116)
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena WebDev | 1625 | 1337 |
| ALE-Bench | 2,041 | 1,245 |
| DeepSWE | 69.9% | — |
| FrontierCode | 53.5% | — |
| SWE-bench Verified (bash only) | — | 66% |
| FrontierSWE | 47% | — |
| SciCode | 61% | — |
| GSO | 78.4% | — |
| WeirdML | 91.9% | — |
| LMArena Coding | 1519 | — |
| MirrorCode | 63.9% | — |
Agentic & Tool Use Claude Fable 5 leads
Claude Fable 5: 54.0 (#2), GPT-5.1-Codex: 38.0 (#33)
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| Terminal-Bench | — | 60.4% |
| APEX-Agents | 63.6% | — |
| Remote Labor Index | 16.1% | — |
| τ²-bench Banking | 39.7% | — |
| PostTrainBench | 41.8% | — |
| GBAEval | 74.5% | — |
| GDP.pdf | 30% | — |
| LMArena Search | 1230 | — |
| METR Time Horizons | — | 70.8% |
| Vending-Bench 2 | 5,680 | — |
Reasoning Not comparable
Claude Fable 5: 76.8 (#6), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| ARC-AGI-2 | 89.2% | — |
| SimpleBench | 81.9% | — |
| Kagi LLM Benchmark | 91.4% | — |
| NYT Connections (extended) | 92.7% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 28.6% | — |
| Chess Puzzles | 41% | — |
| EnigmaEval | 39.3% | — |
| EBR-Bench | 39.5% | — |
| LMArena Hard Prompts | 1508 | — |
| Mystery Game Puzzles | 52% | — |
| DTBench | 98.4% | — |
| LMCA | 61.1% | — |
| Surface Evolver Bench | 95% | — |
| Bench to the Future 3 | 0.13 | — |
| Epoch Capabilities Index | 162.06 | — |
Math Claude Fable 5 leads
Claude Fable 5: 88.5 (#5), GPT-5.1-Codex: 30.3 (#235)
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| ProofBench | 95% | 9% |
| FrontierMath (Tiers 1-3) | 87% | — |
| FrontierMath Tier 4 | 90.2% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| LMArena Math | 1519 | — |
| FrontierMath Erdős | 0% | — |
Knowledge Not comparable
Claude Fable 5: 62.2 (#25), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| GPQA Diamond | 85.9% | — |
| SimpleQA Verified | 70.7% | — |
| LMArena Expert | 1534 | — |
Multimodal Not comparable
Claude Fable 5: 45.3 (#17), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Vision | 1324 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 35.8% | — |
| LMArena Document | 1496 | — |
Multilingual Not comparable
Claude Fable 5: 57.3 (#9), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Non-English | 1481 | — |
| LMArena Chinese | 1543 | — |
| LMArena French | 1505 | — |
| LMArena German | 1486 | — |
| LMArena Japanese | 1506 | — |
| LMArena Korean | 1488 | — |
| LMArena Russian | 1504 | — |
| LMArena Spanish | 1498 | — |
Instruction Following Not comparable
Claude Fable 5: 78.6 (#8), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Instruction Following | 1502 | — |
Long Context Not comparable
Claude Fable 5: 46.3 (#23), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Longer Query | 1509 | — |
Writing & Preference Not comparable
Claude Fable 5: 75.9 (#5), GPT-5.1-Codex: —
| Benchmark | Claude Fable 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Text | 1491 | — |
| LMArena Creative Writing | 1494 | — |
| EQ-Bench Creative Writing | 1943 | — |
| EQ-Bench 4 | 1340 | — |
| LMArena Multi-Turn | 1504 | — |
Frequently asked questions
Is Claude Fable 5 better than GPT-5.1-Codex?
Claude Fable 5 is the stronger model overall, scoring 66.8 to 38.6 on the Noometry Index. GPT-5.1-Codex costs 5.8× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 5 or GPT-5.1-Codex?
GPT-5.1-Codex is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; Claude Fable 5 lists at $10 and $50.
Is Claude Fable 5 or GPT-5.1-Codex better for coding?
Claude Fable 5 scores higher on coding benchmarks: 70.6 versus 41.9 in the Noometry coding category.
Which has the bigger context window?
Claude Fable 5 does, with 1M tokens against 400K.
How many benchmarks do Claude Fable 5 and GPT-5.1-Codex share?
3 benchmarks have published results for both models. Claude Fable 5 has 62 scored results on Noometry and GPT-5.1-Codex has 6.